Ballistisen simuloinnin liikeidean kehittämismahdollisuudet

Asevaikutusta laukaisusta kohteeseen simuloiva integroitu laskentaketju koostuu sisä-, ulko- ja maaliballistiikan malleista. Ulkoballistiikka kattaa laskentamallit radanlaskennan, sääkorjauksen ja ammusaerodynamiikan alueilla. Graafisella käyttöliittymällä toteutetulla, fysikaalisesti tarkkaan mallinnukseen perustuvalla ja kokonaisuuden kattavalla laskentajärjestelmällä on kasvavaa tarvetta teknisiä ja koulutuksellisia tarkoituksia varten. Erikoisesti, jos laskentaketjuun lisätään räjähdysvaikutuksen mallintaminen, voidaan simuloida asejärjestelmien vaikutusta kohteessa käyttäjien arvostamalla tavalla. Tietointensiiviset ballistiikan laskentamallit ovat välttämättömiä työkaluja teknisen suunnitteluosaamisen kattamiseksi ja kilpailuedun luomiseksi verkostoituneessa yritysympäristössä. Yliopistotutkimuksen tuottamien laskennallisten menetelmien hyötykäyttö yritysten suunnittelujärjestelmissä syventää teknistä osaamista, jolla on myös henkilöstöä motivoiva vaikutus teknisesti vaikeutuvilla markkinoilla. Työssä arvioidaan toimialaa analysoimalla eri käyttötarpeita samoille tietokantoihin tukeutuville laskentamalleille. Tarkastellaan teknisiä perusteita, käyttöympäristöjä ja markkinoita liiketoimintamahdollisuuksien tunnistamiseksi. Työn tuloksena syvennetään näkemystä ydinosaamisista ja visioidaan liikeidean erottumista kilpailijoista, markkinoita ja sen kehittämistä.

Nutritional status of Eucalyptus grandis clones evaluated by critical level and DRIS methods

Nutritional status of eight 1.0 and 4.7 years old clones of Eucalyptus grandis, cultivated in a medium textured Ustults - US - and a Quartzipsamments - PS - soils, in Lençóis Paulista, São Paulo, were evaluated by the Diagnosis and Recommendation Integrated System (DRIS) and Critical Level (CL) methods. Based on multivariate discriminant analysis, the DRIS indices described the nutritional status of trees better in relation to tree age and soil type than in relation to nutrient composition. Spearman's correlation coefficients showed statistically significant relationships between volumetric tree growth and nutrients when applying DRIS indices or foliar nutrient concentrations. However, the DRIS indices indicated a lower number of trees with nutritional deficiencies, in relation to the CL method. According to the CL method, P, S, and Ca were deficient in the majority of the soils and tree age categories. By the DRIS method, Ca was the only deficient nutrient in PS soils, and appeared to be particularly limited in one-year-old trees. In conclusion, the DRIS method was more efficient than the CL method in evaluating the nutritional status of eucalyptus trees.

Methods for construction and analysis of computational models in systems biology : applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.

Evaluation of the surface erosion from different timber yarding methods in Honduras

Surface runoff and sediment production from different timber yarding practices, some using Best Management Practices (BMPs) recommended for Honduras, were monitored in experimental plots during the rainy seasons of two consecutive years in pine forest highlands of central Honduras. Different timber yarding systems were applied to pseudo-replicated plots during the rainy seasons of 1999 and 2000. In 1999, two treatments were studied: tractor yarding and skyline cable (a recommended BMP). In 2000, four treatments were evaluated: tractor skidding, skyline cable, animal skidding (another recommended BMP), and undisturbed forest (reference). During the rainy seasons of these years, surface runoff volumes and sediment yield were measured at five 1.5m x 10m erosion plots in each treated area. The results showed significant differences between traditional tractor yarding and the recommended skyline cable and animal skidding methods. Tractor yarding produced six to ten times more erosion during the rainy seasons than cable and animal yarding. The improved soil retention of cable and animal yarding was especially important during September when the highest rainfall occurred in this climate.

Luminescence-based assay methods in drug discovery

The drug discovery process is facing new challenges in the evaluation process of the lead compounds as the number of new compounds synthesized is increasing. The potentiality of test compounds is most frequently assayed through the binding of the test compound to the target molecule or receptor, or measuring functional secondary effects caused by the test compound in the target model cells, tissues or organism. Modern homogeneous high-throughput-screening (HTS) assays for purified estrogen receptors (ER) utilize various luminescence based detection methods. Fluorescence polarization (FP) is a standard method for ER ligand binding assay. It was used to demonstrate the performance of two-photon excitation of fluorescence (TPFE) vs. the conventional one-photon excitation method. As result, the TPFE method showed improved dynamics and was found to be comparable with the conventional method. It also held potential for efficient miniaturization. Other luminescence based ER assays utilize energy transfer from a long-lifetime luminescent label e.g. lanthanide chelates (Eu, Tb) to a prompt luminescent label, the signal being read in a time-resolved mode. As an alternative to this method, a new single-label (Eu) time-resolved detection method was developed, based on the quenching of the label by a soluble quencher molecule when displaced from the receptor to the solution phase by an unlabeled competing ligand. The new method was paralleled with the standard FP method. It was shown to yield comparable results with the FP method and found to hold a significantly higher signal-tobackground ratio than FP. Cell-based functional assays for determining the extent of cell surface adhesion molecule (CAM) expression combined with microscopy analysis of the target molecules would provide improved information content, compared to an expression level assay alone. In this work, immune response was simulated by exposing endothelial cells to cytokine stimulation and the resulting increase in the level of adhesion molecule expression was analyzed on fixed cells by means of immunocytochemistry utilizing specific long-lifetime luminophore labeled antibodies against chosen adhesion molecules. Results showed that the method was capable of use in amulti-parametric assay for protein expression levels of several CAMs simultaneously, combined with analysis of the cellular localization of the chosen adhesion molecules through time-resolved luminescence microscopy inspection.

Bayesian methods for estimation, optimization and experimental design

Mathematical models often contain parameters that need to be calibrated from measured data. The emergence of efficient Markov Chain Monte Carlo (MCMC) methods has made the Bayesian approach a standard tool in quantifying the uncertainty in the parameters. With MCMC, the parameter estimation problem can be solved in a fully statistical manner, and the whole distribution of the parameters can be explored, instead of obtaining point estimates and using, e.g., Gaussian approximations. In this thesis, MCMC methods are applied to parameter estimation problems in chemical reaction engineering, population ecology, and climate modeling. Motivated by the climate model experiments, the methods are developed further to make them more suitable for problems where the model is computationally intensive. After the parameters are estimated, one can start to use the model for various tasks. Two such tasks are studied in this thesis: optimal design of experiments, where the task is to design the next measurements so that the parameter uncertainty is minimized, and model-based optimization, where a model-based quantity, such as the product yield in a chemical reaction model, is optimized. In this thesis, novel ways to perform these tasks are developed, based on the output of MCMC parameter estimation. A separate topic is dynamical state estimation, where the task is to estimate the dynamically changing model state, instead of static parameters. For example, in numerical weather prediction, an estimate of the state of the atmosphere must constantly be updated based on the recently obtained measurements. In this thesis, a novel hybrid state estimation method is developed, which combines elements from deterministic and random sampling methods.

Novel force control methods in a teleoperation system of a hydraulic slider

The objective of the this research project is to develop a novel force control scheme for the teleoperation of a hydraulically driven manipulator, and to implement an ideal transparent mapping between human and machine interaction, and machine and task environment interaction. This master‘s thesis provides a preparatory study for the present research project. The research is limited into a single degree of freedom hydraulic slider with 6-DOF Phantom haptic device. The key contribution of the thesis is to set up the experimental rig including electromechanical haptic device, hydraulic servo and 6-DOF force sensor. The slider is firstly tested as a position servo by using previously developed intelligent switching control algorithm. Subsequently the teleoperated system is set up and the preliminary experiments are carried out. In addition to development of the single DOF experimental set up, methods such as passivity control in teleoperation are reviewed. The thesis also contains review of modeling of the servo slider in particular reference to the servo valve. Markov Chain Monte Carlo method is utilized in developing the robustness of the model in presence of noise.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

On the impact of rigorous approaches on the quality of development

Software systems are expanding and becoming increasingly present in everyday activities. The constantly evolving society demands that they deliver more functionality, are easy to use and work as expected. All these challenges increase the size and complexity of a system. People may not be aware of a presence of a software system, until it malfunctions or even fails to perform. The concept of being able to depend on the software is particularly significant when it comes to the critical systems. At this point quality of a system is regarded as an essential issue, since any deficiencies may lead to considerable money loss or life endangerment. Traditional development methods may not ensure a sufficiently high level of quality. Formal methods, on the other hand, allow us to achieve a high level of rigour and can be applied to develop a complete system or only a critical part of it. Such techniques, applied during system development starting at early design stages, increase the likelihood of obtaining a system that works as required. However, formal methods are sometimes considered difficult to utilise in traditional developments. Therefore, it is important to make them more accessible and reduce the gap between the formal and traditional development methods. This thesis explores the usability of rigorous approaches by giving an insight into formal designs with the use of graphical notation. The understandability of formal modelling is increased due to a compact representation of the development and related design decisions. The central objective of the thesis is to investigate the impact that rigorous approaches have on quality of developments. This means that it is necessary to establish certain techniques for evaluation of rigorous developments. Since we are studying various development settings and methods, specific measurement plans and a set of metrics need to be created for each setting. Our goal is to provide methods for collecting data and record evidence of the applicability of rigorous approaches. This would support the organisations in making decisions about integration of formal methods into their development processes. It is important to control the software development, especially in its initial stages. Therefore, we focus on the specification and modelling phases, as well as related artefacts, e.g. models. These have significant influence on the quality of a final system. Since application of formal methods may increase the complexity of a system, it may impact its maintainability, and thus quality. Our goal is to leverage quality of a system via metrics and measurements, as well as generic refinement patterns, which are applied to a model and a specification. We argue that they can facilitate the process of creating software systems, by e.g. controlling complexity and providing the modelling guidelines. Moreover, we find them as additional mechanisms for quality control and improvement, also for rigorous approaches. The main contribution of this thesis is to provide the metrics and measurements that help in assessing the impact of rigorous approaches on developments. We establish the techniques for the evaluation of certain aspects of quality, which are based on structural, syntactical and process related characteristics of an early-stage development artefacts, i.e. specifications and models. The presented approaches are applied to various case studies. The results of the investigation are juxtaposed with the perception of domain experts. It is our aspiration to promote measurements as an indispensable part of quality control process and a strategy towards the quality improvement.

First dice your dill – new methods and techniques in sample handling

This book is dedicated to celebrate the 60th birthday of Professor Rainer Huopalahti. Professor Rainer “Repe” Huopalahti has had, and in fact is still enjoying a distinguished career in the analysis of food and food related flavor compounds. One will find it hard to make any progress in this particular field without a valid and innovative sample handling technique and this is a field in which Professor Huopalahti has made great contributions. The title and the front cover of this book honors Professor Huopahti’s early steps in science. His PhD thesis which was published on 1985 is entitled “Composition and content of aroma compounds in the dill herb, Anethum graveolens L., affected by different factors”. At that time, the thesis introduced new technology being applied to sample handling and analysis of flavoring compounds of dill. Sample handling is an essential task that in just about every analysis. If one is working with minor compounds in a sample or trying to detect trace levels of the analytes, one of the aims of sample handling may be to increase the sensitivity of the analytical method. On the other hand, if one is working with a challenging matrix such as the kind found in biological samples, one of the aims is to increase the selectivity. However, quite often the aim is to increase both the selectivity and the sensitivity. This book provides good and representative examples about the necessity of valid sample handling and the role of the sample handling in the analytical method. The contributors of the book are leading Finnish scientists on the field of organic instrumental analytical chemistry. Some of them are also Repe’ s personal friends and former students from the University of Turku, Department of Biochemistry and Food Chemistry. Importantly, the authors all know Repe in one way or another and are well aware of his achievements on the field of analytical chemistry. The editorial team had a great time during the planning phase and during the “hard work editorial phase” of the book. For example, we came up with many ideas on how to publish the book. After many long discussions, we decided to have a limited edition as an “old school hard cover book” – and to acknowledge more modern ways of disseminating knowledge by publishing an internet version of the book on the webpages of the University of Turku. Downloading the book from the webpage for personal use is free of charge. We believe and hope that the book will be read with great interest by scientists working in the fascinating field of organic instrumental analytical chemistry. We decided to publish our book in English for two main reasons. First, we believe that in the near future, more and more teaching in Finnish Universities will be delivered in English. To facilitate this process and encourage students to develop good language skills, it was decided to be published the book in English. Secondly, we believe that the book will also interest scientists outside Finland – particularly in the other member states of the European Union. The editorial team thanks all the authors for their willingness to contribute to this book – and to adhere to the very strict schedule. We also want to thank the various individuals and enterprises who financially supported the book project. Without that support, it would not have been possible to publish the hardcover book.

Test Campaign Parameter Editor for a Graphical TTCN-3 Development Environment

This paper presents the design for a graphical parameter editor for Testing and Test Control Notation 3 (TTCN-3) test suites. This work was done in the context of OpenTTCN IDE, a TTCN-3 development environment built on top of the Eclipse platform. The design presented relies on an additional parameter editing tab added to the launch configurations for test campaigns. This parameter editing tab shows the list of editable parameters and allows opening editing components for the different parameters. Each TTCN-3 primitive type will have a specific editing component providing tools to ease modification of values of that type.